The events of Sep. 11, 2001 focused the efforts of various public and private stakeholders on homeland security. Identified threats include terrorist and criminal activities, accidents and natural disasters. As described below, threats occurring on or alongside water are particularly challenging as waterways are vast in extent with large numbers of recreational and commercial vessels.
Terrorist and criminal activities can be carried out using low-flying general aviation aircraft, and vessels of all sizes from large container ships down to zodiacs and jet-skis. When the water is frozen over, snow-mobiles and vehicles add to the target mix. Awareness of what these uncooperative targets are doing at any given time and understanding whether particular target behavior is suspicious and requires closer examination is what we mean by situational awareness. Protecting people and property from threats requires situational awareness that provides authorities and citizens with timely information to prevent, respond to, and mitigate them.
From a temporal standpoint, threats can occur at any time, day or night, and are infrequent; therefore situational awareness is needed 24/7/365. Furthermore, because threats can unfold in just seconds (e.g. a vessel crosses a narrow waterway such as the St. Lawrence River and lands on the shoreline of another country violating an international border, or a vessel enters a marine exclusion zone on the waterside of a nuclear power plant on Lake Ontario), persistent surveillance is needed to provide adequate situational awareness.
From a spatial perspective, threats can occur anywhere across our vast waterways. Canada's coastline spans over 200,000 km and the world's coastlines total 356,000 km. Worldwide, commercially navigated waterways are estimated at over 670,000 km. North American international borders along waterways exceed 6,000 km and there are over 20,000 km of actively maintained commercial inland and intra-coastal waterways. The Great Lakes St. Lawrence Seaway System alone spans 3,700 km in length bringing goods to/from dozens of ports with an international border running through it, and serving an area of North American that is home to about two-thirds of Canada's population and industries, and one-quarter of the United States'.
With this background, manufacturers have responded with the development of affordable, wide-area surveillance RINs which are in the early stages of deployment to provide the required situational awareness to stakeholders. See T. J. Nohara, “A Commercial Approach to Successful Persistent Radar Surveillance of Sea, Air and Land Along the Northern Border”, 2010 IEEE International Conference on Technologies for Homeland Security, 8-10 Nov. 2010, Waltham, Mass., for an overview. All radars referenced therein are candidates for improvement with the present invention. These radars include surface-mounted radars including inexpensive and fixed, marine radars, agile radars and air traffic control radars, military radars, mobile radars, ship-based radars and aerostat radars.
In parallel with the above development, researchers have begun studying ways to develop knowledge-aided systems for use in adaptive radars with the hope of better performance. The underlying idea here is to allow radar processing algorithms to adapt on the fly (instead of being hard-coded) to improve detection performance; in a word, to add an “intelligence-like” capability to a radar. A book by Joseph Guerci entitled Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, Artech House, 2010 provides a treatment of knowledge-aided adaptive radars directed primarily to expensive, coherent, military radars with multi-element antennas and multi-channel receivers such as airborne GMTI (ground moving target indication) radars. This work exploits the fact that land clutter, including large discrete reflectors (e.g. bridges, train tracks), nonhomogeneous littoral clutter and highways with numerous vehicles cause problems for adaptive radar processing algorithms that rely only on radar measurements. His approach is to exploit prior, external, geospatial knowledge of these scattering features by predicting ahead a few seconds where the airborne radar will be looking and altering the radar processing algorithms accordingly to account for the geospatial characteristics that will be encountered there.
The IEEE Signal Processing Magazine, Volume 23, Number 1, January 2006 devotes an entire issue to this subject, including a paper from Simon Haykin entitled “Cognitive radar: a way of the future” where a bat's echo-location applied to tracking and homing in on an insect (dinner) motivated the idea of a closed feedback circuit between the transmitter, the environment and the receiver of a radar. Haykin identifies a wide-area radar network as a challenging problem and questions how to design one with cognition. This same sentiment is echoed in his article, Point of View: Cognitive Dynamic Systems, Special Issue, Proceedings of the IEEE, Volume 100, Number 7, July 2012.
Haykin subsequently provides a principled and theoretical foundation for developing cognitive dynamic systems in his book Cognitive Dynamic Systems, Perception-Action Cycle, Radar And Radio, Cambridge University Press, England, March 2012. He formalizes cognitive radar as needing to be based on the functioning of the human brain to be truly cognitive; and affirms the perception-action-cycle, memory, and the characteristics of attention and intelligence as necessary features of cognition. Attention and intelligence are algorithmic in nature and left as loose ideas that require application-specific future development. On a more practical level, Haykin focuses on the single radar, single target tracking problem with the objective of developing cognition to improve track quality for which he demonstrates feasibility through some basic computer simulations.
The invention described herein builds on this prior work by developing cognitive radar information networks, extending Nohara's RINs and Haykin's ideas on cognitive dynamic systems.